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Data Preprocessing with Pandas Collection

A collection of data preprocessing code snippets to prepare tabular data using Pandas for analysis, machine learning or visualisation

Import Data

CSV

Selecting the Row that Contains The Column Header

Reading a Subset of Columns

Skipping Rows

Reading a Sample of Rows

Parsing a Date Column

EXCEL

Import an Excel Sheet

Select the Header Row

Selecting Columns to Import

Skipping Rows

Selecting the Number of Rows

Import Columns from Excel as Dates

SCRAPE DATA

Initialise a Web Scraper with Beautiful Soup

Find All Instances of a Tag with Beautiful Soup

Find the Nth Tag On a WebPage with Beautiful Soup

Get An Inner Tag Using Beautiful Soup

Get The Text Within a Tag Using Beautiful Soup

Using Selectors in Beautiful Soup to Scrape Using Classes & IDs

Prepare Data

CONVERTING

Efficient Data Type Minification in Python using Numpy and Pandas

Converting Data Types

CLEANING NANS

Replacing NaNs

Grouped Forward Fill & Back Fill

Fill NaNs With Values & By Series

CLEANING STRINGS

Find & Replace

Changing the Case of String Columns

Removing Whitespace or Characters

SELECTING & RENAMING

Selecting Columns Using Loc and iLoc

Dropping Columns

Renaming Columns Using Dictionaries & Lists

Selecting Rows Using iLoc

SAMPLING

Stratified Sampling

Regular Sampling

FILTERING

Filtering a Dataframe Using AND

Filtering a Dataframe Using OR

Drop Duplicate Values

Filter a DataFrame Using a List

Transform

SUMMARISE

Pivoting Dataframes

Aggregate Using GroupBy, Agg & Dictionaries

Join

MERGE

How to Combine or Merge Pandas Dataframe Columns

Join DataFrames Using Merge

UNION

Union Two DataFrames

Feature Engineering

WINDOW & LAG FEATURES

Running Total

Lag Features Using Shift

Grouped Rolling Features

STRINGS

Find & Replace

Get The First & Last N Characters

DATES

Extract Date & Time Features

Weekend Flag

Days Between Dates

Finding the Dates a Number of Days Before & After

STATISTICS & FORMULAS

Common Statistics

Absolute Values

Round, Ceiling & Floor

Modulus of Values in a DataFrame

Creating a Column of Random Numbers